Many decision-making processes face continuously changing environments. For example, processes like producing oil and gas from reservoirs usually involve changing environments that cannot be generalized easily. Decision support systems or process control systems are often customized for individual operating environments. There are best practices in place, which often are changed and adapted to cope with individual challenges when operating oil and gas reservoirs on a case-by-case basis.
In conventional oil and gas production processes, data-conditioning workflows are typically not in place, and human production workflows are typically not centrally managed or appropriately automated. Data flow from sensors to applications and model validation can be major bottlenecks in real-time environments. While data streams in oil and gas production often go real-time, corresponding workflow execution typically lags behind or even breaks. Expert and user knowledge is not well captured in such distributed decision support fragments for use in future analysis. In addition, decision-making processes often depend on user knowledge and individual experience, therefore each situation can lead to non-standardized workflows. Decision support systems often cannot readily cope with changing business and operating environments. Ultimately, operators can lose business opportunities due to poor asset awareness.